Robert Kern wrote:
>
> Since there are only 6 places where PyMemData_RENEW is used, all 6
> uses should be benchmarked. I would prefer a more targeted benchmark
> so we know exactly what we are measuring.
>
Ok, I started a new branch for aligned allocator:
http://projects.scipy.org/scipy/numpy/br
Hey,
The trunk is in pretty good shape and it is about time that I put out
an official release. So tomorrow (in a little over twelve hours) I am
going to create a 1.1.x branch and the trunk will be officially open
for 1.2 development. If there are no major issues that show up at the
last minute,
2008/5/5 David Cournapeau <[EMAIL PROTECTED]>:
> Basically, what I have in mind is, in a first step (for numpy 1.2):
> - define functions to allocate on a given alignement
> - make PyMemData_NEW 16 byte aligned by default (to be compatible
> with SSE and co).
>
> The problem was, and st
Dear Robert,
Thank you. But i am trying to install it in a 32-bit machine only. In that
case, why dose it require 64 bit libraries.
Bala
On Mon, May 5, 2008 at 10:47 PM, Robert Kern <[EMAIL PROTECTED]> wrote:
> On Mon, May 5, 2008 at 6:14 AM, Bala subramanian
> <[EMAIL PROTECTED]> wrote:
> > Dea
Hello all,
I wanted to fix the formatting problems on the wiki page
http://scipy.org/scipy/numpy/wiki/MaskedArrayApiChanges, so I followed
the instructions on http://scipy.org/scipy/numpy/wiki (which state "In
order to edit wiki pages or create and edit tickets, you need to
register first.")
But e
Nadav Horesh schreef:
> I think you have a problem of overflow in r5: You may better use utin64
> instead of uint32.
>
> Nadav.
>
>
Nadav,
My problems were due to trying to do two things at once.
The code below does what I want and it is very fast. I see the power of
numpy now:
import numpy
Anne Archibald wrote:
>
> How much does this matter? I mean, what if you simply left all the
> reallocs as-is? The arrays that resulted from reallocs would not
> typically be aligned, but we cannot in any case expect all arrays to
> be aligned.
The problem would be the interaction between the alig
Hello,
I encountered the error "Segmentation fault (core dumped)" during a rather
standard multiplication, without excessive memory us. This looks likes a
bug to me?
I am using Python 2.5, Numpy 1.0.4 under Ubuntu 7.10.
Here is what I am doing: i have two arrays, points1 and points2.
points1.sh
ti, 2008-05-06 kello 14:15 +0200, Marius Nijhuis kirjoitti:
> Hello,
>
> I encountered the error "Segmentation fault (core dumped)" during a
> rather standard multiplication, without excessive memory us. This
> looks likes a bug to me?
> I am using Python 2.5, Numpy 1.0.4 under Ubuntu 7.10.
>
On Tue, 6 May 2008, Jarrod Millman apparently wrote:
> open tickets that I would like everyone to take a brief
> look at:
> http://projects.scipy.org/scipy/numpy/ticket/760
My understanding is that my patch, which would give
a deprecation warning, was rejected in favor of the patch
specified at
Hi nice numpy people
I was wondering if anyone could shed some light on how to distinguish an
empty array of a given shape and an zeros array of the same dimensions.
Thanks
Andy
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On Tue, May 6, 2008 at 9:31 AM, Andy Cheesman <[EMAIL PROTECTED]>
wrote:
> Hi nice numpy people
>
> I was wondering if anyone could shed some light on how to distinguish an
> empty array of a given shape and an zeros array of the same dimensions.
An empty array is just uninitialized, while a zer
I'm trying to design a labeled array class. A labeled array contains a
2d array and two lists. One list labels the rows of the array (e.g.
variable names) and another list labels the columns of the array (e.g.
dates).
You can sum (or multiply, divide, subtract, etc.) two labeled arrays
that have d
2008/5/6 Andy Cheesman <[EMAIL PROTECTED]>:
> I was wondering if anyone could shed some light on how to distinguish an
> empty array of a given shape and an zeros array of the same dimensions.
An "empty" array, that is, an array returned by the function empty(),
just means an uninitialized arra
On Tue, May 6, 2008 at 9:45 AM, Anne Archibald
<[EMAIL PROTECTED]> wrote:
> In fact, if you want to use empty() down the road, it may
> make sense to initialize your array to zeros()/0., so that if you ever
> use the values, the NaNs will propagate and become obvious.
Numpy has ones and zeros.
On Tue, May 6, 2008 at 9:53 AM, Keith Goodman <[EMAIL PROTECTED]> wrote:
> On Tue, May 6, 2008 at 9:45 AM, Anne Archibald
> <[EMAIL PROTECTED]> wrote:
> > In fact, if you want to use empty() down the road, it may
> > make sense to initialize your array to zeros()/0., so that if you ever
> > use
On Tue, May 6, 2008 at 10:03 AM, Timothy Hochberg <[EMAIL PROTECTED]> wrote:
> Why don't you just roll your own?
>
> >>> def nans(shape, dtype=float):
> ... a = np.empty(shape, dtype)
> ... a.fill(np.nan)
> ... return a
> ...
> >>> nans([3,4])
> array([[ NaN, NaN, NaN, NaN],
>
On Tue, May 6, 2008 at 1:00 PM, "Keith Goodman" <[EMAIL PROTECTED]> wrote:
> I'm trying to design a labeled array class. A labeled array contains a
> 2d array and two lists. One list labels the rows of the array (e.g.
> variable names) and another list labels the columns of the array (e.g.
>
Hi all,
I'm currently working on a function that converts a
sympy (http://code.google.com/p/sympy) expression to a lambda-function.
In this lambda-function all sympy builtin functions are replaced by
numpy functions, since they are faster.
Now it may happen that users pass sympy-symbols like pi t
What is .T? It looks like an attribute, behaves like a method, and
smells like magic. I'd like to add it to my class but don't no where
to begin.
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On Tue, May 6, 2008 at 2:22 PM, Keith Goodman <[EMAIL PROTECTED]> wrote:
> What is .T? It looks like an attribute, behaves like a method, and
> smells like magic. I'd like to add it to my class but don't no where
> to begin.
It is a property. It returns the transpose of the array. If you had a
.
On Tue, May 6, 2008 at 12:28 PM, Robert Kern <[EMAIL PROTECTED]> wrote:
>
> On Tue, May 6, 2008 at 2:22 PM, Keith Goodman <[EMAIL PROTECTED]> wrote:
> > What is .T? It looks like an attribute, behaves like a method, and
> > smells like magic. I'd like to add it to my class but don't no where
>
On Tue, May 6, 2008 at 4:21 AM, Bala subramanian
<[EMAIL PROTECTED]> wrote:
> Dear Robert,
> Thank you. But i am trying to install it in a 32-bit machine only. In that
> case, why dose it require 64 bit libraries.
Well, judging from the paths on the command line, Python thinks it is
on a 64-bit ma
On Tue, May 6, 2008 at 4:33 AM, Vincent Noel <[EMAIL PROTECTED]> wrote:
> Hello all,
>
> I wanted to fix the formatting problems on the wiki page
> http://scipy.org/scipy/numpy/wiki/MaskedArrayApiChanges, so I followed
> the instructions on http://scipy.org/scipy/numpy/wiki (which state "In
> o
On Tue, May 6, 2008 at 6:40 AM, Alan G Isaac <[EMAIL PROTECTED]> wrote:
> On Tue, 6 May 2008, Jarrod Millman apparently wrote:
> > open tickets that I would like everyone to take a brief
> > look at:
> > http://projects.scipy.org/scipy/numpy/ticket/760
>
> My understanding is that my patch, which
2008/5/6 Charles R Harris <[EMAIL PROTECTED]>:
>
> On Tue, May 6, 2008 at 6:40 AM, Alan G Isaac <[EMAIL PROTECTED]> wrote:
> >
> > On Tue, 6 May 2008, Jarrod Millman apparently wrote:
> > > open tickets that I would like everyone to take a brief
> > > look at:
> > > http://projects.scipy.org/scipy/
Hi,
I think Ticket 605 (Incorrect behaviour of numpy.histogram) can be closed.
With regards to Ticket 706 (scalar indexing of matrices -> deprecation
warning) I think it should not be a blocker now but should apply the
next version. There were many different issues (and threads) raised in
the cont
>>> a = numpy.array([[1,2,6], [2,2,8], [2,1,7],[1,1,5]])
>>> a
array([[1, 2, 6],
[2, 2, 8],
[2, 1, 7],
[1, 1, 5]])
>>> indices = numpy.lexsort(a.T)
>>> a.T.take(indices,axis=-1).T
array([[1, 1, 5],
[1, 2, 6],
[2, 1, 7],
[2, 2, 8]])
The above does what I w
2008/5/6 Eleanor <[EMAIL PROTECTED]>:
> >>> a = numpy.array([[1,2,6], [2,2,8], [2,1,7],[1,1,5]])
> >>> a
> array([[1, 2, 6],
>[2, 2, 8],
>[2, 1, 7],
>[1, 1, 5]])
> >>> indices = numpy.lexsort(a.T)
> >>> a.T.take(indices,axis=-1).T
> array([[1, 1, 5],
>[1, 2, 6],
Anne Archibald gmail.com> writes:
>
> It appears that lexsort is broken in several ways, and its docstring
> is misleading.
>
> First of all, this code is not doing quite what you describe. The
> primary key here is the [5,6,7,8] column, followed by the middle and
> then by the first. This is a
I have just created the 1.1.x branch:
http://projects.scipy.org/scipy/numpy/changeset/5134
In about 24 hours I will tag the 1.1.0 release from the branch. At
this point only critical bug fixes should be applied to the branch.
The trunk is now open for 1.2 development.
Thanks,
--
Jarrod Millman
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